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Record W2052774206 · doi:10.1109/icton.2013.6602747

Effect of the composition of Au<inf>x</inf>Ag<inf>(1−x)</inf> nanoalloys on their nonlinear optical response

2013· article· en· W2052774206 on OpenAlexaff
Irène Papagiannouli, Stelios Couris, David Rioux, Michel Meunier

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicLaser-Ablation Synthesis of Nanoparticles
Canadian institutionsPolytechnique Montréal
FundersFonds National de la Recherche Luxembourg
KeywordsSurface plasmon resonanceAnalytical Chemistry (journal)FemtosecondLaserNanoparticlePhysicsStereochemistryMaterials scienceChemistryNanotechnologyOpticsOrganic chemistry

Abstract

fetched live from OpenAlex

In the present work the nonlinear optical response of some AuxAg(1-x)alloy nanoparticles (NPs) prepared by a femtosecond laser ablation process is studied using Z-scan technique employing 4 ns, 532 nm laser pulses. The prepared NPs with diameters of 15 - 20 nm, had different compositions, i.e. gold molar fractions (GMF) x, ranging from x = 0 (pure Ag) to x = 1 (pure Au) and they were exhibiting surface plasmon resonance (SPR) peak whose spectral position and strength were varying depending on GMF. The AuxAg(1-x)NPs were found to exhibit negative nonlinear refraction, corresponding to self-defocusing behavior and negligible nonlinear absorption. The nonlinear optical response of the AuxAg(1-x)alloy nanoparticles was found to be strongly dependent on the GMF of the nanoalloy, since the surface plasmon resonance peak enhances the nonlinear optical response of the metallic nanoalloys when it is close to the excitation wavelength.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.221
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2013
Admission routes1
Has abstractyes

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